Topic: drift-diffusion model

Cognitive neuroscience studies routinely concentrate on calculating the correlation coefficient between trial-averaged Event-Related Potentials (ERPs) and behavioral performance such as response time and accuracy. However there are some disadvantages in this traditional approach: 1) ignoring the variance of EEG data across trials, 2) requiring a large number of participants to find robust inferences, and 3) a lack of formal cognitive models to explain cognition. In this work, we used the drift-diffusion model to decompose perceptual decision making to underlying latent variables to explain be

Cognitive models of timing often include a pacemaker analogue whose ticks are accumulated to form an internal representation of time, and a threshold that determines when a target duration has elapsed. However, clear EEG manifestations of these abstract components have not yet been identified. We measured the EEG of subjects while they performed a temporal bisection task in which they were requested to categorize visual stimuli as short or long in duration. We report an ERP component whose amplitude depends monotonically on the stimulus duration. The relation of the ERP amplitude and stimulus

Interval timing is a fundamental component action, and is susceptible to motor-related temporal distortions. Previous studies have shown that movement biases temporal estimates, but have primarily considered self-modulated movement only. However, real-world encounters often include situations in which movement is restricted or perturbed by environmental factors. In the following experiments, we introduced viscous movement environments to externally modulate movement and investigated the resulting effects on temporal perception. In two separate tasks, participants timed auditory intervals while